The global Machine learning methods to Materials Science is still recent, a lot of published applications are quite basic in nature and complexity. Often, they involve fitting models to extremely small training sets or even applying machine learning methods to composition spaces that could possibly be mapped out in hundreds of CPU hours. It is of course possible to use machine learning methods as a simple fitting procedure for small low-dimensional datasets. However, this does not play to their strength and will not allow us to replicate the success machine learning for Material Science methods had in other fields.
All accepted abstracts will be published in respective Allied Academies Journals.
Abstracts will be provided with Digital Object Identifier by
